Infrared cameras are utilized in a variety of imaging applications to capture infrared images. These captured infrared images may be grainy (e.g., noisy) or lack sufficient detail and, therefore to some extent, processing techniques may be applied to suppress unwanted features, such as noise, and/or refine the captured infrared images.
In general, infrared cameras may have to deal with two often contradictory signal characteristics. On the one hand, a digitized infrared image may have a large dynamic range, which may be measured in digital units (e.g., on the order of tens of thousands of digital units). Within this dynamic range, some faint detail might be of great importance to the user and which, in order to be visible to the user on a display, may require for example the application of a contrast enhancement filter. On the other hand, an infrared image may also suffer from poor signal to noise ratio (SNR) and consequently, contrast enhancement might make the image less useful because an enhancement to the contrast may result also in the amplification of the noise. Typically, some kind of noise filter may be applied to the infrared signal, but finding the right settings for the noise filter for a particular imager, for a particular scene, and for a particular application may be time consuming. Therefore, minimizing the user's time for finding the optimal setting, under which some detail or target of choice may best be viewed, may be very beneficial for a number of different types of applications.
A drawback of a conventional infrared camera is that a user is not allowed to control these processing techniques during capture of the image or the optimal settings may be difficult to determine by the user. Consequently, from a user's perspective, the result is a less than desirable image being captured and displayed. Furthermore, automatically setting various parameters may be difficult. For example, for two images with similar signal properties (e.g., SNR, dynamic range, etc.), the fainter details may be essential for classifying a target or may just be clutter that the user would rather suppress than enhance.
As a result, there is a need for improved techniques for providing image processing techniques and/or user-controllable settings for infrared cameras.